Trend analysis of indicators: a comparison of recent changes in the status of marine ecosystems around the world
Bibliographic record
Abstract
Abstract Blanchard, J. L., Coll, M., Trenkel, V. M., Vergnon, R., Yemane, D., Jouffre, D., Link, J. S., and Shin, Y-J. 2010. Trend analysis of indicators: a comparison of recent changes in the status of marine ecosystems around the world. – ICES Journal of Marine Science, 67: 732–744. Time-series of ecological and exploitation indicators collected from 19 ecosystems were analysed to investigate whether there have been temporal trends in the status of fish communities. Using linear and non-linear statistical methods, trends are reported for six indicators (mean length of fish in the community, mean lifespan, proportion of predatory fish, total biomass of surveyed species, mean trophic level of landings, and inverse fishing pressure), and the redundancy of these indicators across ecosystems is evaluated. The expected direction of change for an ecosystem that is increasingly impacted by fishing is a decline in all indicators. A mixture of negative and positive directions of change is recorded, both within and among all ecosystems considered. No consistent patterns in the redundancy of the ecological indicators across ecosystems emerged from the analyses, confirming that each indicator provided complementary information on ecosystem status. The different trends in indicators may reflect differing historical exploitation patterns, management, and environmental regimes in these systems. Commitment to monitoring programmes and development of system-specific baseline, target, and threshold reference levels are required. Improved understanding of the responsiveness and performance of ecological indicators to management actions are needed to address adequately whether ecosystems are recovering from, or being further impacted by, fishing, and whether management targets are being met. The relative effects of multiple environmental and ecological processes as well as multiple human-induced stressors that characterize exploited ecosystems also need to be quantified.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".